• Computers and Concrete
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• 제8권3호
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• pp.279-292
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• 2011

The main purpose of this study includes investigation of the rheological properties of fresh self consolidating cement paste containing chemical and mineral additives using Artificial Neural Network (ANN) model. In order to develop the model, 200 different mixes are cast in the laboratory as a part of an extensive experimental research program. The data used in the ANN model are arranged in a format of fourteen input parameters covering water-binder ratio, four different mineral additives (calcium carbonate, metakaolin, silica fume, and limestone), five different superplasticizers based on the poly carboxylate and naphthalene and four different Viscosity Modified Admixtures (VMAs). Two common output parameters including the mini slump value and flow cone time are chosen for measuring the rheological properties of fresh self consolidating cement paste. Having validated the model, the influence of effective parameters on the rheological properties of fresh self consolidating cement paste is investigated based on the ANN model outputs. The output results of the model are then compared with the results of previous studies performed by other researchers. Ultimately, the analysis of the model outputs determines the optimal percentage of additives which has a strong influence on the rheological properties of fresh self consolidating cement paste. The proposed ANN model shows that metakaolin and silica fume affect the rheological properties in the same manner. In addition, for providing the suitable rheological properties, the ANN model introduces the optimal percentage of metakaolin, silica fume, calcium carbonate and limestone as 15, 15, 20 and 20% by cement weight, respectively.

• The korean journal of orthodontics
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• 제54권5호
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• pp.316-324
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• 2024

Objective: To evaluate tooth displacement and periodontal stress generated by the dual action vertical intra-arch technique (DAVIT) for open-bite correction using three-dimensional finite element analysis. Methods: A three-dimensional model of the maxilla was created by modeling the cortical bone, cancellous bone, periodontal ligament, and teeth from the second molar to the central incisor of a hemiarch. All orthodontic devices were designed using specific software to reproduce their morpho-dimensional characteristics, and their physical properties were determined using Young's modulus and Poisson's coefficient of each material. A linear static simulation was performed to analyze the tooth displacements (mm) and maximum stresses (Mpa) induced in the periodontal ligament by the posterior intrusion and anterior extrusion forces generated by the DAVIT. Results: The first and second molars showed the greatest intrusion, whereas the canines and lateral incisors showed the greatest extrusion displacement. A neutral zone of displacement corresponding to the fulcrum of occlusal plane rotation was observed in the premolar region. Buccal tipping of the molars and lingual tipping of the anterior teeth occurred with intrusion and extrusion, respectively. Posterior intrusion generated compressive stress at the apex of the buccal roots and furcation of the molars, while anterior extrusion generated tensile stress at the apex and apical third of the palatal root surface of the incisors and canines. Conclusions: DAVIT mechanics produced a set of beneficial effects for open-bite correction, including molar intrusion, extrusion and palatal tipping of the anterior teeth, and occlusal plane rotation with posterior teeth uprighting.

• Journal of Intelligence and Information Systems
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• 제24권4호
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

• Korean Journal of Health Education and Promotion
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• 제23권3호
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• pp.99-119
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• 2006

Objectives: This study intends to understand the difference within group of social support level and the effect of social support to health behaviors and health status of the elderly by selecting the old of local society as target. Methods: Data were obtained from self-administered questionnaire of 8,688 persons, older than 65 years, living in a community. We measured the sociodemographic characteristics, social support(family support, other support, quality of support), physical health state(subjective health status, number of chronic disease), physical function state(activities of daily living; ADL, instrumental activities of daily living; IADL), cognition state(mini-mental state examination-Korean; MMSE-K) and depression state(short form of geriatric depression scale; SGDS), health behaviors(smoking, drinking, exercise, eating habit). Univariate, multinominal logistic regression and covariance structure analysis were employed to analyze factors affecting on the social support of the elderly. Results: When considering the degree of social support by the sociodemographic characteristics of the older adults, the family support, other support and quality of support is better when the old is male, young, high education and self-reported living status is good and it has significance statistically. When considering the relation between social support and health status, the family support, other support and quality of support is better when the old's subjective and objective physical health status is good. The family support, other support and quality of support is better when the old's subjective health status is better. The other support and quality of support is better when the old's ADL(activities of daily living) and IADL(instrumental activities of daily living) are good. The family support, other support and quality of support is better when the old's cognitive function and depression state is better. When considering the relation between social support and health behaviors, in case of smoking and drinking, the quality of support, family support and other support is better when the old smokes and drinks rather than the old does not. In case of exercise and eating habit, the family support, other support and quality of support is better when the old exercises and eats regularly rather than the old does not. It has significance statistically. From the result of performing covariance structure analysis by structural equation modeling(SEM) with two endogenous variable(health behaviors and health status) and one exogenous variable(social support), factor loading of health status is 0.74 and factor loading of health behaviors is 0.05. The social support explains health status of 55.4% and health behaviors of 2.9%. Conclusions: This study has the meaning that it finds the difference of social support generating from inside of the group for the old residing in city and country and specifies the effect that the difference of social support influences to health status and health behaviors. From now on, in the development of health improvement strategy of the olds, it is necessary to approach from inclusive aspect while considering psychosocial factor such as social support and social economical factor as well as health status.

• Asia pacific journal of information systems
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• 제18권2호
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• pp.41-72
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• 2008

The purpose of this study is the investigation of the effects of user participation, network effect, social influence, and usefulness on stickiness and continued use on Internet communities. In this research, stickiness refers to repeat visit and visit duration to an Internet community. Continued use means the willingness to continue to use an Internet community in the future. Internet community-based companies can earn money through selling the digital contents such as game, music, and avatar, advertizing on internet site, or offering an affiliate marketing. For such money making, stickiness and continued use of Internet users is much more important than the number of Internet users. We tried to answer following three questions. Fist, what is the effects of user participation on stickiness and continued use on Internet communities? Second, by what is user participation formed? Third, are network effect, social influence, and usefulness that was significant at prior research about technology acceptance model(TAM) still significant on internet communities? In this study, user participation, network effect, social influence, and usefulness are independent variables, stickiness is mediating variable, and continued use is dependent variable. Among independent variables, we are focused on user participation. User participation means that Internet user participates in the development of Internet community site (called mini-hompy or blog in Korea). User participation was studied from 1970 to 1997 at the research area of information system. But since 1997 when Internet started to spread to the public, user participation has hardly been studied. Given the importance of user participation at the success of Internet-based companies, it is very meaningful to study the research topic of user participation. To test the proposed model, we used a data set generated from the survey. The survey instrument was designed on the basis of a comprehensive literature review and interviews of experts, and was refined through several rounds of pretests, revisions, and pilot tests. The respondents of survey were the undergraduates and the graduate students who mainly used Internet communities. Data analysis was conducted using 217 respondents(response rate, 97.7 percent). We used structural equation modeling(SEM) implemented in partial least square(PLS). We chose PLS for two reason. First, our model has formative constructs. PLS uses components-based algorithm and can estimated formative constructs. Second, PLS is more appropriate when the research model is in an early stage of development. A review of the literature suggests that empirical tests of user participation is still sparse. The test of model was executed in the order of three research questions. First user participation had the direct effects on stickiness(${\beta}$=0.150, p<0.01) and continued use (${\beta}$=0.119, p<0.05). And user participation, as a partial mediation model, had a indirect effect on continued use mediated through stickiness (${\beta}$=0.007, p<0.05). Second, optional participation and prosuming participation significantly formed user participation. Optional participation, with a path magnitude as high as 0.986 (p<0.001), is a key determinant for the strength of user participation. Third, Network effect (${\beta}$=0.236, p<0.001). social influence (${\beta}$=0.135, p<0.05), and usefulness (${\beta}$=0.343, p<0.001) had directly significant impacts on stickiness. But network effect and social influence, as a full mediation model, had both indirectly significant impacts on continued use mediated through stickiness (${\beta}$=0.11, p<0.001, and ${\beta}$=0.063, p<0.05, respectively). Compared with this result, usefulness, as a partial mediation model, had a direct impact on continued use and a indirect impact on continued use mediated through stickiness. This study has three contributions. First this is the first empirical study showing that user participation is the significant driver of continued use. The researchers of information system have hardly studies user participation since late 1990s. And the researchers of marketing have studied a few lately. Second, this study enhanced the understanding of user participation. Up to recently, user participation has been studied from the bipolar viewpoint of participation v.s non-participation. Also, even the study on participation has been studied from the point of limited optional participation. But, this study proved the existence of prosuming participation to design and produce products or services, besides optional participation. And this study empirically proved that optional participation and prosuming participation were the key determinant for user participation. Third, our study compliments traditional studies of TAM. According prior literature about of TAM, the constructs of network effect, social influence, and usefulness had effects on the technology adoption. This study proved that these constructs still are significant on Internet communities.

• Nuclear Medicine and Molecular Imaging
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• 제41권4호
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• pp.317-325
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• 2007

Purpose: Biological parameters can be quantified using dynamic PET data with compartment modeling and Nonlinear Least Square (NLS) estimation. However, the generation of parametric images using the NLS is not appropriate because of the initial value problem and excessive computation time. In irreversible model, Patlak graphical analysis (PGA) has been commonly used as an alternative to the NLS method. In PGA, however, the start time ($t^*$, time where linear phase starts) has to be determined. In this study, we suggest a new Multiple Linear Analysis for irreversible radiotracer (MLAIR) to estimate fluoride bone influx rate (Ki). Methods: $[^{18}F]Fluoride$ dynamic PET scans was acquired for 60 min in three normal mini-pigs. The plasma input curve was derived using blood sampling from the femoral artery. Tissue time-activity curves were measured by drawing region of interests (ROls) on the femur head, vertebra, and muscle. Parametric images of Ki were generated using MLAIR and PGA methods. Result: In ROI analysis, estimated Ki values using MLAIR and PGA method was slightly higher than those of NLS, but the results of MLAIR and PGA were equivalent. Patlak slopes (Ki) were changed with different $t^*$ in low uptake region. Compared with PGA, the quality of parametric image was considerably improved using new method. Conclusion: The results showed that the MLAIR was efficient and robust method for the generation of Ki parametric image from $[^{18}F]Fluoride$ PET. It will be also a good alternative to PGA for the radiotracers with irreversible three compartment model.